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arXiv 2020年

作者： Liu, Dongchen Wang, Junzheng Wang, Shoukun The National Key Laboratory of Complex System Intelligent Control and Decision School of Automation Beijing Institute of Technology Beijing10081 China The Ministry of Industry and Information Technology Key Laboratory of Servo Motion System Drive and Control School of Automation Beijing Institute of Technology Beijing10081 China

This work investigates the coordinated motion control and obstacle-crossing problem for a four wheel-leg independent motor-driven robotic system via a model predictive control (MPC) approach based on an event-triggering mechanism. The modeling of a wheel-leg robotic control system with a dynamic supporting polygon is organized. The system dynamic model is 3 degrees of freedom ignoring the pitch, roll, and vertical motions. The single wheel dynamic is analyzed considering the characteristics of the motor-driven and the Burckhardt nonlinear tire model. As a result, an over-actuated predictive model is proposed with the motor torques as inputs and the system states as outputs. As the supporting polygon is only adjusted at certain conditions, an event-based triggering mechanism is designed to save hardware resources and energy. The MPC controller is evaluated on a virtual prototype as well as a physical prototype. The simulation results guide the parameter tuning for the controller implementation in the physical prototype. The experimental results on these two prototypes verify the efficiency of the proposed approach. © 2020, CC BY.

关键词： Geometry

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Observer-based finite time H ∞ control of nonlinear discrete time-varying systems with an adaptive event-triggered Mechanism

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Journal of the Franklin Institute 2020年第16期357卷 11668-11689页

作者： Menghua Chen Hamid Reza Karimi Jian Sun School of Automation Beijing Institute of Technology Beijing 100081 China Department of Mechanical Engineering Politecnico di Milano Milan 20156 Italy Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing 100081 China

The problem of finite time stability and synthesis is discussed for nonlinear discrete time-varying systems by using the T-S fuzzy model. To reduce the communication network resources, two adaptive event-triggered mechanisms (AETMs) are taken into consideration in sensor-to-observer (S/O) and observer-to-controller (O/C) channels. The thresholds of the AETMs are adjusted according to the estimation error rather than some fixed ones. Sufficient conditions for developing an observer-based time-varying control are obtained, which ensure the time-varying error system to be finite time stable and satisfy the H ∞ performance simultaneously. Moreover, using the singular value decomposition technique, recursive linear matrix inequalities conditions are obtained for computing the gains of the controller and observer. Finally, the superiority and applicability of the proposed method are demonstrated by examples.

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Forward Modeling of Shallow Transient Electromagnetic Method under Ramp Turn-off Current

Forward Modeling of Shallow Transient Electromagnetic Method...

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第三十九届中国控制会议

作者： Guangjun Wang Menglan Song School of Automation China University of Geosciences China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex System

In order to reduce the shallow detection blind zone and improve the shallow detection accuracy, this paper presents a shallow transient electromagnetic direct forward modeling method based on ramp turn-off current. The main idea is to obtain the spectrum of the ramp turn-off current signal by Fourier transform at first, then using Maxwell’s equation to solve the propagation process of the electromagnetic signal in the medium, thus obtaining the early signal of transient electromagnetic *** theory, this method is more suitable for the detection of shallow subsurface media than the ideal step signal. Simulation experiments on the ramp step signals with different turn-off times show that the complete ideal coincidence with the traditional ideal step signal when the turn-off time approaches zero, indicating the correctness of the algorithm. At the same time, compared with the current element superposition forward method, the forward curve obtained by this method is closer to the actual situation,and the calculation speed is much faster than the current element superposition method. The research results in this paper are of great value to reduce the detection blind zone, improve the detection accuracy and real-time performance of the transient electromagnetic detecting.

关键词： Ramp turn-off current shallow transient electromagnetic method forward modeling

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Robust recognition of truck license plate in mine environment

Robust recognition of truck license plate in mine environmen...

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2020 International Conference on Computer Engineering and intelligent control, ICCEIC 2020

作者： Shi, Siqi Li, Nanting Ma, Yanjun Zheng, Liping Xi'An University of Technology Key Laboratory of Shaanxi Province for Complex System Control and Intelligent Information Processing Xian China Xi'An University of Technology School of Electrical Engineering Xian China Xi'An University of Technology School of Automatic and Information Engineering Xian China

ISBN: (数字)9781728185736

ISBN: (纸本)9781728185736

To improve the decreased recognition performance for truck license plate in complex mine environment, which is caused by such factors as polluted, damaged, a robust license plate recognition method is proposed. Firstly, several candidate locations of license plate in the truck image are obtained by utilizing features of both edge and color. Furthermore, the parameter of license plate area intersection ratio is defined to find the precise localization among those above candidates. Then, a character segmentation scheme based on the gray projection method and morphological operator is used to remove those interference factors, such as frame, rivet and stain and uneven illumination. Finally, to increase the robustness of characters recognition by CNN, a self-built license plate character dataset is constructed, which contains various polluted samples obtained by manual simulation. As shown by the experimental results, the proposed method has higher accuracy in license plate location, and obtains an improvement on character recognition accuracy by 4% compared to other existed methods. © 2020 IEEE.

关键词： License plates (automobile)

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Improved Magnetic Coupling Resonance Wireless Power Transfer system

Improved Magnetic Coupling Resonance Wireless Power Transfer...

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第三十九届中国控制会议

作者： Guangjun Wang Jianhui Sun School of Automation China University of Geosciences China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex System

For the power supply of spaceborne cameras on two-body satellites, an improved magnetic coupling resonant wireless power transfer system(WPT) is proposed. By establishing the equivalent circuit model of WPT system, the influence of topology model and high-Q repeating coil on system performance is analyzed. Finally, the correctness of theory and analysis was verified by experiments. The experimental results show that when the transmission distance of the improved WPT system is 11 cm, the load can receive 18.66 W of power and the transmission efficiency is 69%. Compared with the traditional two-coil WPT system,the system has a significant improvement in transmission distance, transmission power, and transmission efficiency, and can meet the technical requirements of spaceborne cameras in transmission distance, transmission power and transmission efficiency.

关键词： Magnetic coupling resonance WPT Transmission distance Transmission power Transmission efficiency

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Content based image retrieval via sparse representation and feature fusion 8

Content based image retrieval via sparse representation and ...

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8th IEEE Data Driven control and Learning systems Conference, DDCLS 2019

作者： Liu, Han Wang, Wenqing Jiao, Pengfei Shanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'An University of Technology Xi'an710048 China

ISBN: (纸本)9781728114545

During the last two decades, content-based image retrieval (CBIR) has been widely studied. The limitations of low-level feature representation of images have been a thorny issue in image retrieval problems. In this paper, a CBIR algorithm based on sparse representation and feature fusion is proposed, in which global features and local features are combined to retrieve the images. Firstly, the GIST features are used to roughly retrieve the images with similar scene information by measuring Canberra distance. Then, a representation of the local features extracted from the rough retrieval results is obtained by sparse coding and feature pooling. Finally, Euclidean distance is used to measure the similarity of the sparse feature vectors to obtain the retrieval results. The proposed method is tested on the Coil20 and Caltech256 image datasets. The experimental results demonstrate that the proposed algorithm can achieve comparable superior retrieval performance to the existing single feature-based image retrieval algorithms. © 2019 IEEE.

关键词： Image fusion

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An Approximated Domination Relationship based on Binary Classifiers for Evolutionary Multiobjective Optimization

An Approximated Domination Relationship based on Binary Clas...

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Congress on Evolutionary Computation

作者： Hao Hao Aimin Zhou Hu Zhang Shanghai Key Laboratory of Multidimensional Information Processing School of Computer Science and Technology East China Normal University Shanghai China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-mechanical Engineering Institute Beijing China

Preselection is an important strategy to improve evolutionary algorithms’ performance by filtering out unpromising solutions before fitness evaluations. This paper introduces a pre-selection strategy based on an approximated Pareto domination relationship for multiobjective evolutionary optimization. For each objective, a binary relation between each pair of solutions is constructed based on the current population, and a binary classifier is built based on the binary relation pairs. In this way, an approximated Pareto domination relationship can be defined. When new trial solutions are generated, the approximated Pareto domination is used to select promising solutions, which shall be evaluated by the real objective functions. The new preselection is integrated into two algorithms. The experimental results on two benchmark test suites suggest that the algorithms with preselection outperform their original ones.

关键词： Filtering Computational modeling Sociology Training data Evolutionary computation Approximation algorithms Linear programming

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S4TP: Social-Suitable and Safety-Sensitive Trajectory Planning for Autonomous Vehicles

arXiv

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arXiv 2024年

作者： Wang, Xiao Tang, Ke Dai, Xingyuan Xu, Jintao Du, Quancheng Ai, Rui Wang, Yuxiao Gu, Weihao Engineering Research Center of Autonomous Unmanned System Technology Ministry of Education Anhui University Hefei230031 China Haomo Technology Co. Ltd. Beijing100192 China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Qingdao Academy of Intelligent Industries Qingdao266114 China The School of Computer and Communication Engineering University of Science and Technology Beijing Beijing100083 China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China

In public roads, autonomous vehicles (AVs) face the challenge of frequent interactions with human-driven vehicles (HDVs), which render uncertain driving behavior due to varying social characteristics among humans. To effectively assess the risks prevailing in the vicinity of AVs in social interactive traffic scenarios and achieve safe autonomous driving, this article proposes a social-suitable and safety-sensitive trajectory planning (S4TP) framework. Specifically, S4TP integrates the Social-Aware Trajectory Prediction (SATP) and Social-Aware Driving Risk Field (SADRF) modules. SATP utilizes Transformers to effectively encode the driving scene and incorporates an AV’s planned trajectory during the prediction decoding process. SADRF assesses the expected surrounding risk degrees during AVs-HDVs interactions, each with different social characteristics, visualized as two-dimensional heat maps centered on the AV. SADRF models the driving intentions of the surrounding HDVs and predicts trajectories based on the representation of vehicular interactions. S4TP employs an optimization-based approach for motion planning, utilizing the predicted HDVs’ trajectories as input. With the integration of SADRF, S4TP executes real-time online optimization of the planned trajectory of AV within low-risk regions, thus improving the safety and the interpretability of the planned trajectory. We have conducted comprehensive tests of the proposed method using the SMARTS simulator. Experimental results in complex social scenarios, such as unprotected left-turn intersections, merging, cruising, and overtaking, validate the superiority of our proposed S4TP in terms of safety and rationality. S4TP achieves a pass rate of 100% across all scenarios, surpassing the current state-of-the-art methods Fanta of 98.25% and Predictive-decision of 94.75%. Copyright © 2024, The Authors. All rights reserved.

关键词： Autonomous vehicles

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An Improved Segmentation Method for Porous Transducer CT Images

An Improved Segmentation Method for Porous Transducer CT Ima...

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2019第十一届数字图像处理国际会议

作者： Meiling Wang Ruoyu Guo Ke Ning Li Ming Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision

The paper presents an improved image segmentation method with a straightforward workflow for porous transducer CT images,which can be used to establish porous transducer three-dimensional model and further study its *** distribution of CT images is firstly analyzed and Gaussian filtering is conducted to reduce divergence of CT *** improved fully convolutional neural network model based on U-Net,for which multi-channel images are set as network input,is trained using training *** proposed method improves pore connectivity of the segmentation *** of porosity and permeability relative errors as well as MIOU on test set shows that the proposed method is an effective and generic two-phase segmentation method for porous transducer CT images without need of adjusting any parameters.

关键词： Porous transducer image segmentation permeability pore connectivity fully convolutional neural network

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Research on Infrared Image Processing Algorithm of Generator Carbon Brush Based on Adaptive Stochastic Resonance Array

Research on Infrared Image Processing Algorithm of Generator...

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2021 China Automation Congress, CAC 2021

作者： Jiao, Shangbin Huang, Weichao Geng, Bo Zhang, Youmin Wu, Xiaohui Wu, Pengyue Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi 'an University of Technology Xi'an710048 China Department of Mechanical Industrial and Aerospace Engineering Concordia University MontrealQCH3G 1M8 Canada Huaneng Weihai Power Generation Co. Ltd Weihai264200 China Xi'an Thermal Power Research Institute Co. Ltd. Xi'an710048 China

ISBN: (纸本)9781665426473

The safe and stable operation of the generator set is related to the national economy and people's livelihood. As an important part of generator excitation system, carbon brush and slip ring temperature monitoring can effectively evaluate the state of the generator, which plays a vital role. Most of the current researches use infrared images to monitor carbon brush temperature, but there are often problems such as high noise and unclear focus. According to the requirements of infrared image display, this paper combines the method of bistable stochastic resonance to denoise the image, and on this basis, introduces the adaptive stochastic resonance array method to denoise the gray image. Experimental results show that compared with common image denoising methods and classic bistable stochastic resonance, the adaptive stochastic resonance array method has improved both visual effects and peak signal-to-noise ratio (PSNR), which further proves the good application of stochastic resonance in weak signal detection and extraction. © 2021 IEEE

关键词： Stochastic systems

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